Python ';螺纹';对象没有属性'_儿童';-django+;scikit学习
我在django应用程序中遇到问题,该应用程序使用随机林分类器()对项目进行分类。我收到的错误是:Python ';螺纹';对象没有属性'_儿童';-django+;scikit学习,python,django,multithreading,scikit-learn,Python,Django,Multithreading,Scikit Learn,我在django应用程序中遇到问题,该应用程序使用随机林分类器()对项目进行分类。我收到的错误是: AttributeError at /items/ 'Thread' object has no attribute '_children' Request Method: POST Request URL: http://localhost:8000/items/ Django Version: 1.7.6 Exception Type: AttributeEr
AttributeError at /items/
'Thread' object has no attribute '_children'
Request Method: POST
Request URL: http://localhost:8000/items/
Django Version: 1.7.6
Exception Type: AttributeError
Exception Value:
'Thread' object has no attribute '_children'
Exception Location: /usr/lib/python2.7/multiprocessing/dummy/__init__.py in start, line 73
Python Executable: /home/cristian/env/bin/python
Python Version: 2.7.3
Python Path:
['/home/cristian/filters',
'/home/cristian/env/lib/python2.7',
'/home/cristian/env/lib/python2.7/plat-linux2',
'/home/cristian/env/lib/python2.7/lib-tk',
'/home/cristian/env/lib/python2.7/lib-old',
'/home/cristian/env/lib/python2.7/lib-dynload',
'/usr/lib/python2.7',
'/usr/lib/python2.7/plat-linux2',
'/usr/lib/python2.7/lib-tk',
'/home/cristian/env/local/lib/python2.7/site-packages']
Server time: Fri, 24 Apr 2015 16:08:20 +0000
问题是我根本没有使用线程。代码如下:
def item_to_dict(item):
item_dict = {}
for key in item:
value = item[key]
# fix encoding
if isinstance(value, unicode):
value = value.encode('utf-8')
item_dict[key] = [value]
return item_dict
def load_classifier(filter_name):
clf = joblib.load(os.path.join(CLASSIFIERS_PATH, filter_name, 'random_forest.100k.' + filter_name.lower() + '.pkl'))
return clf
@api_view(['POST'])
def classify_item(request):
"""
Classify item
"""
if request.method == 'POST':
serializer = ItemSerializer(data=request.data['item'])
if serializer.is_valid():
# get item and filter_name
item = serializer.data
filter_name = request.data['filter']
item_dict = item_to_dict(item)
clf = load_classifier(filter_name)
# score item
y_pred = clf.predict_proba(pd.DataFrame(item_dict))
item_score = y_pred[0][1]
# create and save classification
classification = Classification(classifier_name=filter_name,score=item_score,item_id=item['_id'])
classification_serializer = ClassificationSerializer(classification)
return Response(classification_serializer.data, status=status.HTTP_201_CREATED)
else:
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
我能够打印出“clf”和“item_dict”变量,一切看起来都正常。当我调用分类器的“predict_proba”方法时,会出现错误。
需要补充的一点是,当我第一次运行服务器并发送post方法时,我没有收到错误
以下是完整的回溯:
File "/home/cristian/env/local/lib/python2.7/site-packages/django/core/handlers/base.py" in get_response
line 111. response = wrapped_callback(request, *callback_args, **callback_kwargs)
File "/home/cristian/env/local/lib/python2.7/site-packages/django/views/decorators/csrf.py" in wrapped_view
line 57. return view_func(*args, **kwargs)
File "/home/cristian/env/local/lib/python2.7/site-packages/django/views/generic/base.py" in view
line 69. return self.dispatch(request, *args, **kwargs)
File "/home/cristian/env/local/lib/python2.7/site-packages/rest_framework/views.py" in dispatch
line 452. response = self.handle_exception(exc)
File "/home/cristian/env/local/lib/python2.7/site-packages/rest_framework/views.py" in dispatch
line 449. response = handler(request, *args, **kwargs)
File "/home/cristian/env/local/lib/python2.7/site-packages/rest_framework/decorators.py" in handler
line 50. return func(*args, **kwargs)
File "/home/cristian/filters/classifiers/views.py" in classify_item
line 70. y_pred = clf.predict_proba(pd.DataFrame(item_dict))
File "/home/cristian/env/local/lib/python2.7/site-packages/sklearn/pipeline.py" in predict_proba
line 159. return self.steps[-1][-1].predict_proba(Xt)
File "/home/cristian/env/local/lib/python2.7/site-packages/sklearn/ensemble/forest.py" in predict_proba
line 468. for i in range(n_jobs))
File "/home/cristian/env/local/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py" in __call__
line 568. self._pool = ThreadPool(n_jobs)
File "/usr/lib/python2.7/multiprocessing/pool.py" in __init__
line 685. Pool.__init__(self, processes, initializer, initargs)
File "/usr/lib/python2.7/multiprocessing/pool.py" in __init__
line 136. self._repopulate_pool()
File "/usr/lib/python2.7/multiprocessing/pool.py" in _repopulate_pool
line 199. w.start()
File "/usr/lib/python2.7/multiprocessing/dummy/__init__.py" in start
line 73. self._parent._children[self] = None
Exception Type: AttributeError at /items/
Exception Value: 'Thread' object has no attribute '_children'
作为一种解决方法,您可以在预测时使用以下方法禁用线程:
clf = load_classifier(filter_name)
clf.set_params(n_jobs=1)
y_pred = clf.predict_proba(pd.DataFrame(item_dict))
还要注意的是,在每次请求时调用load\u分类器
可能会很昂贵,因为它实际上是从磁盘加载模型的
您可以将
mmap\u mode='r'
传递到joblib。加载
到内存映射磁盘中的数据。即使有并发请求同时访问相同的模型参数(如果使用gunicorn之类的工具,则使用不同的线程和不同的Python进程),也可以只加载一次模型。这基本上是一个在多处理中的错误
请包括完整的回溯,以便我们能够理解问题的根本原因。